基于协进化多子群蚁群算法的多无人作战飞机协同航迹规划研究

协同航迹规划是有效提高多无人作战飞机( UCAV)协同作战效能的关键技术之一。分析了多UCAV协同航迹规划问题中的空间协同约束、时序约束以及任务时间约束，建立了基于“协同系数”的协同航迹性能评价指标；在此基础上，通过引入蚂蚁子群间的协同进化策略，并对蚁群算法状态转移规则、信息素更新机制进行了改进，设计并实现了基于协进化多子群蚁群算法的协同航迹规划算法。仿真实验结果表明：本文方法能够很好地处理多UCAV协同任务中的各类约束条件，是一种有效的协同航迹规划方法。

Research on Multi-UCAV Cooperative Route Planning Based on Coevolutionary Multi-Ant-Colony Algorithm

Cooperative route planning is one of the key technologies increasing the efficiency of multi unmanned combat aerial vehicles(UCAV)to perform cooperative missions.The space,precedence and time window constraints in multi-UCAV cooperative route planning were analyzed,and the criteria of cooperative route estimation based on cooperative coefficient were presented;The cooperative route planning algorithm based on the coevolutionary multi-ant-colony algorithm was designed and im.plemented by the coevolutionary strategy among multi-ant-colony and the improved state transition ruleand pheromone updating mechanism.The simulated results show that the proposed method can solve the cooperative constraints efficiently,and is effective for the multi-UCAV cooperative route planning problem.